Adam Stein

21 papers A* 3Journal 15Unranked 3
YearRankTypeTitle / Venue / Authors
2025 J jnl
Experience-Guided Adaptation of Inference-Time Reasoning Strategies.
CoRR
Adam Stein, Matthew Trager, Benjamin Bowman, Michael Kleinman, Aditya Chattopadhyay, Wei Xia, Stefano Soatto
2025 J jnl
Instruction Following by Boosting Attention of Large Language Models.
CoRR
Vitoria Guardieiro, Adam Stein, Avishree Khare, Eric Wong
2025 J jnl
Once Upon an Input: Reasoning via Per-Instance Program Synthesis.
CoRR
Adam Stein, Neelay Velingker, Mayur Naik, Eric Wong
2025 J jnl
SuperActivators: Only the Tail of the Distribution Contains Reliable Concept Signals.
CoRR
Cassandra Goldberg, Chaehyeon Kim, Adam Stein, Eric Wong
2025 J jnl
The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models.
CoRR
Adam Stein, Aaditya Naik, Neelay Velingker, Mayur Naik, Eric Wong
2025 — conf
Towards Style Alignment in Cross-Cultural Translation.
ACL (1)
Shreya Havaldar, Adam Stein, Eric Wong, Lyle H. Ungar
2025 J jnl
Towards Style Alignment in Cross-Cultural Translation.
CoRR
Shreya Havaldar, Adam Stein, Eric Wong, Lyle H. Ungar
2025 J jnl
Where's the Bug? Attention Probing for Scalable Fault Localization.
CoRR
Adam Stein, Arthur Wayne, Aaditya Naik, Mayur Naik, Eric Wong
2024 J jnl
TorchQL: A Programming Framework for Integrity Constraints in Machine Learning.
Proc. ACM Program. Lang.
Aaditya Naik, Adam Stein, Yinjun Wu, Mayur Naik, Eric Wong
2024 A* conf
Towards Compositionality in Concept Learning.
ICML
Adam Stein, Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong
2024 J jnl
Towards Compositionality in Concept Learning.
CoRR
Adam Stein, Aaditya Naik, Yinjun Wu, Mayur Naik, Eric Wong
2023 — conf
Faithful Chain-of-Thought Reasoning.
IJCNLP (1)
Qing Lyu, Shreya Havaldar, Adam Stein, Li Zhang, Delip Rao, Eric Wong, Marianna Apidianaki, Chris Callison-Burch
2023 J jnl
Faithful Chain-of-Thought Reasoning.
CoRR
Qing Lyu, Shreya Havaldar, Adam Stein, Li Zhang, Delip Rao, Eric Wong, Marianna Apidianaki, Chris Callison-Burch
2023 A* conf
Learning to Select Pivotal Samples for Meta Re-weighting.
AAAI
Yinjun Wu, Adam Stein, Jacob R. Gardner, Mayur Naik
2023 J jnl
Learning to Select Pivotal Samples for Meta Re-weighting.
CoRR
Yinjun Wu, Adam Stein, Jacob R. Gardner, Mayur Naik
2023 J jnl
MDB: Interactively Querying Datasets and Models.
CoRR
Aaditya Naik, Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik
2023 J jnl
Rectifying Group Irregularities in Explanations for Distribution Shift.
CoRR
Adam Stein, Yinjun Wu, Eric Wong, Mayur Naik
2023 J jnl
Relational Query Synthesis ⋈ Decision Tree Learning.
Proc. VLDB Endow.
Aaditya Naik, Aalok Thakkar, Adam Stein, Rajeev Alur, Mayur Naik
2023 — conf
TopEx: Topic-based Explanations for Model Comparison.
Tiny Papers @ ICLR
Shreya Havaldar, Adam Stein, Eric Wong, Lyle H. Ungar
2023 J jnl
TopEx: Topic-based Explanations for Model Comparison.
CoRR
Shreya Havaldar, Adam Stein, Eric Wong, Lyle H. Ungar
2018 A* conf
Attribution Inference for Digital Advertising using Inhomogeneous Poisson Models.
WWW
Zachary Nichols, Adam Stein